package ‘topdownr’ -...

Package ‘topdownr’July 8, 2020

Title Investigation of Fragmentation Conditions in Top-Down Proteomics

Version 1.10.0

Description The topdownr package allows automatic and systemic investigationof fragment conditions. It creates Thermo Orbitrap Fusion Lumos methodfiles to test hundreds of fragmentation conditions. Additionally itprovides functions to analyse and process the generated MS data anddetermine the best conditions to maximise overall fragment coverage.

Depends R (>= 3.5), methods, BiocGenerics (>= 0.20.0), ProtGenerics(>= 1.10.0), Biostrings (>= 2.42.1), S4Vectors (>= 0.12.2)

Imports grDevices, stats, tools, utils, Biobase, Matrix (>= 1.2.10),MSnbase (>= 2.3.10), ggplot2 (>= 2.2.1), mzR (>= 2.11.4)

Suggests topdownrdata (>= 0.2), knitr, ranger, testthat, BiocStyle,xml2

License GPL (>= 3)

URL https://github.com/sgibb/topdownr/

BugReports https://github.com/sgibb/topdownr/issues/

LazyData true

VignetteBuilder knitr

Roxygen list(markdown=TRUE)

RoxygenNote 7.0.2

biocViews ImmunoOncology, Infrastructure, Proteomics,MassSpectrometry, Coverage

Encoding UTF-8

git_url https://git.bioconductor.org/packages/topdownr

git_branch RELEASE_3_11

git_last_commit 0a6ce60

git_last_commit_date 2020-04-27

Date/Publication 2020-07-07

Author Sebastian Gibb [aut, cre] (<https://orcid.org/0000-0001-7406-4443>),Pavel Shliaha [aut] (<https://orcid.org/0000-0003-3092-0724>),Ole Nørregaard Jensen [aut] (<https://orcid.org/0000-0003-1862-8528>)

Maintainer Sebastian Gibb <[email protected]>

1

https://github.com/sgibb/topdownr/

https://github.com/sgibb/topdownr/issues/

2 topdownr-package

R topics documented:topdownr-package . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2AbstractTopDownSet-class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3createExperimentsFragmentOptimisation . . . . . . . . . . . . . . . . . . . . . . . . . 7createTngFusionMethFiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10expandMs1Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11FragmentViews-class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12NCBSet-class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14readTopDownFiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17tds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19topdownr-deprecated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20TopDownSet-class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20validMs1Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24writeMethodXmls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Index 27

topdownr-package Investigation of Fragmentation Conditions in Top-Down Proteomics

Description

The topdownr package allows automatic and systemic investigation of fragment conditions. It cre-ates Thermo Orbitrap Fusion Lumos method files to test hundreds of fragmentation conditions.Additionally it provides functions to analyse and process the generated MS data and determine thebest conditions to maximise overall fragment coverage.

Details

The usage of the topdownr package is demonstrated in the following vignettes:

• Generate .meth files prior data acquisition for the Thermo Orbitrap Fusion Lumos MS devise:vignette("data-generation",package="topdownr").

• How to analyse top-down fragmenation data: vignette("analysis",package="topdownr")

Author(s)

Sebastian Gibb <[email protected]>, Pavel Shliaha <[email protected]>, Ole Nørre-gaard Jensen <[email protected]>

References


See Also

Useful links:

• https://github.com/sgibb/topdownr/

• Report bugs at https://github.com/sgibb/topdownr/issues/



https://github.com/sgibb/topdownr/issues/

AbstractTopDownSet-class 3

AbstractTopDownSet-class

The AbstractTopDownSet class

Description

Abstract/VIRTUAL parent class for TopDownSet and NCBSet to provide common interface.

Usage

## S4 method for signature 'AbstractTopDownSet,ANY,ANY,ANY'x[i, j, ..., drop = FALSE]

## S4 method for signature 'AbstractTopDownSet,ANY,missing'x[[i, j, ...]]

## S4 replacement method for signature 'AbstractTopDownSet,ANY,missing'x[[i, j, ...]] <- value

## S4 method for signature 'AbstractTopDownSet'x$name

## S4 replacement method for signature 'AbstractTopDownSet'x$name <- value

## S4 method for signature 'AbstractTopDownSet'assayData(object)

## S4 method for signature 'AbstractTopDownSet'colData(object)

## S4 replacement method for signature 'AbstractTopDownSet'colData(object, ...) <- value

## S4 method for signature 'AbstractTopDownSet,AbstractTopDownSet'combine(x, y)

## S4 method for signature 'AbstractTopDownSet'conditionData(object, ...)

## S4 replacement method for signature 'AbstractTopDownSet'conditionData(object, ...) <- value

## S4 method for signature 'AbstractTopDownSet'conditionNames(object)

## S4 method for signature 'AbstractTopDownSet'dim(x)

## S4 method for signature 'AbstractTopDownSet'dimnames(x)

4 AbstractTopDownSet-class

## S4 method for signature 'AbstractTopDownSet'removeEmptyConditions(object)

## S4 method for signature 'AbstractTopDownSet'rowViews(object, ...)

## S4 method for signature 'AbstractTopDownSet'show(object)

## S4 method for signature 'AbstractTopDownSet'summary(object, what = c("rows", "columns"), ...)

## S4 method for signature 'AbstractTopDownSet'updateConditionNames(object,sampleColumns = c("Mz", "AgcTarget", "EtdReagentTarget", "EtdActivation","CidActivation", "HcdActivation", "UvpdActivation"),

verbose = interactive())

## S4 method for signature 'AbstractTopDownSet'updateMedianInjectionTime(object,by = list(Mz = object$Mz, AgcTarget = object$AgcTarget)

)

Arguments

i, j numeric, logical or character, indices specifying elements to extract or re-place.

drop logical, currently ignored.

value replacment value.

name character name of an (non)existing column in colData.

object, x AbstractTopDownSet

y AbstractTopDownSet

what character, specifies whether "rows" or "columns" should be summarized.

sampleColumns character, column names of the colData() used to define a sample (technicalreplicate). This is used to add the Sample column (used for easier aggregation,etc.).

verbose logical, verbose output?

by list, grouping information.

... arguments passed to internal/other methods.

Details

This class just provides a common interface. It is not intended for direct use by the user. Please seeTopDownSet for an example usage of its child class.

AbstractTopDownSet-class 5

Value

This is an Abstract/VIRTUAL class to provide a common interface for TopDownSet and NCBSet. Itis not possible to create an AbstractTopDownSet object.

Methods (by generic)

• [: Subset operator.For i numeric, logical or character vectors or empty (missing) or NULL are supported.Subsetting is done on the fragment/bond (row) level. character indices could be names(e.g. c("a1","b1","c1","c2","c3")) or types (e.g. c("c","x")) of the fragments for Top-DownSet objects, or names of the bonds (e.g. c("bond001")) for NCBSet objects.j could be a numeric or logical vector and subsetting is done on the condition/run (column)level.

• [[: Subset operator.i could be a numeric or logical vector and subsetting is done on the condition/run (column)level.

• [[<-: Setter for a column in the colData slot.The [[<- operator is used to add/replace a single column of the colData DataFrame.

• $: Accessor for columns in the colData slot.The $ simplifies the accession of a single column of the colData. It is identical to the [[operator.

• $<-: Setter for a column in the colData slot.The $<- operator is used to add/replace a single column of the colData DataFrame. It isidentical to the [[<- operator.

• assayData: Accessor for the assay slot.Returns a Matrix::dgCMatrix that stores the intensity/coverage information of AbstractTop-DownSet object.

• colData: Accessor for the colData slot.Returns a S4Vectors::DataFrame that stores metadata for the conditons/runs (columns) of theAbstractTopDownSet object.

• colData<-: Setter for the colData slot.Replaces metadata for the conditons/runs (columns) of the AbstractTopDownSet object.

• combine: Combine AbstractTopDownSet objects.combine allows to combine two or more AbstractTopDownSet objects. Please note that ituses the default sampleColumns to define technical replicates (see readTopDownFiles()).andthe default by argument to group ion injection times for the calculation of the median time(see updateMedianInjectionTime()). Both could be modified after combine by callingupdateConditionNames() (with modified sampleColumns argument) and updateMedianInjectionTime()(with modified by argument).

• conditionData: Accessor for the colData slot.An alias for colData.

• conditionData<-: Setter for the colData slot.An alias for colData<-.

• conditionNames: Accessor for condition names.Returns a character with names for the conditions/runs (columns).

• dim: Accessor for dimensions.Returns a numeric with number of fragments/bonds (rows) and conditions/runs (columns).

6 AbstractTopDownSet-class

• dimnames: Accessor for dimension names.

Returns a list with names for the fragments/bonds (rows) and for the conditions/runs (columns).

• removeEmptyConditions: Remove empty conditions/runs.

Removes conditions/runs (columns) without any intensity/coverage information from the Ab-stractTopDownSet object. It returns a modified AbstractTopDownSet object.

• rowViews: Accessor for the rowViews slot.

Depending on the implementation it returns an FragmentViews object for TopDownSet objectsor an Biostrings::XStringViews object for NCBSet objects.

• summary: Summary statistics.

Returns a matrix with some statistics: number of fragments, total/min/first quartile/median/mean/thirdquartile/maximum of intensity values.

• updateConditionNames: Update condition names.

Updates condition names based on sampleColumns from conditionData/colData. Columnswith just identical entries are ignored. This method will create/update the colData(object)$Samplecolumn that identifies technical replicates and could be used in other methods.

• updateMedianInjectionTime: Update median ion injection times.

Recalculates median ion injection times by a user given grouping variable (default: Mz, Agc-Target). This is useful if you acquire new data and the ion injection time differs acrossthe runs. Use the by argument to provide a list/data.frame of grouping variables, e.g.by=colData(object)[,c("Mz","AgcTarget","File")].

Slots

rowViews Biostrings::XStringViews, information about fragments/bonds (name, type, sequence,mass, charge), see Biostrings::XStringViews and FragmentViews for details.

colData S4Vectors::DataFrame, information about the MS2 experiments and the fragmentationconditions.

assay Matrix::dgCMatrix, intensity/coverage values of the fragments/bonds. The rows correspondto the fragments/bonds and the columns to the condition/run. It just stores values that aredifferent from zero.

files character, files that were imported.

processing character, log messages.

Author(s)

Sebastian Gibb <[email protected]>

See Also

• TopDownSet and NCBSet which both implement/use this interface. These manual pages alsoprovide some example code.

• FragmentViews (and Biostrings::XStringViews) for the row view interface.

• Matrix::dgCMatrix for technical details about the intensity/coverage storage.

createExperimentsFragmentOptimisation 7

Examples

## Because AbstractTopDownSet is a VIRTUAL class we could not create any## object of it. Here we demonstrate the usage with an TopDownSet that## implements the AbstractTopDownSet interface. See `?"TopDownSet-class"` for## more details an further examples.

## Example datadata(tds, package="topdownr")

tds

head(summary(tds))

# Accessing slotsrowViews(tds)colData(tds)head(assayData(tds))

# Accessing colDatatds$Mztds$FilterString

# Subsetting

# First 100 fragmentstds[1:100]

# All c fragmentstds["c"]

# Just c 152tds["c152"]

# Condition 1 to 10tds[, 1:10]

createExperimentsFragmentOptimisation

Create fragment optimisation experiment

Description

This function is used to create a tree-like list of all combinations of a user-given set of MS1 andTMS2 settings for an fragment optimisation experiment. The list could be written to an OrbitrapFusion Lumos method xml file using writeMethodXmls().

Usage

createExperimentsFragmentOptimisation(ms1,...,groupBy = c("AgcTarget", "replication"),nMs2perMs1 = 10,

8 createExperimentsFragmentOptimisation

scanDuration = 0,replications = 2,randomise = TRUE

)

Arguments

ms1 data.frame, MS1 settings.

... further named arguments with data.frames containing the TMS2 settings.

groupBy character, group experiments by columns in the TMS2 data.frames. Thecolumns have to be present in all data.frames. Each group will be written toits own XML file.

nMs2perMs1 integer, how many TMS2 scans should be run after a MS1 scan?

scanDuration double, if greater than zero (e.g. scanDuration=0.5) the Start/EndTimeMinare overwritten with a duration of scanDuration. If scanDuration is zero(default) Start/EndTimeMin are not overwritten.

replications integer, number of replications.

randomise logical, should the TMS2 scan settings randomised?

Value

list, able to be written via xml2::as_xml_document()

See Also

writeMethodXmls(), expandMs1Conditions(), expandTms2Conditions()

Examples

## build experiments within Rms1 <- expandMs1Conditions(

FirstMass=400,LastMass=1200,Microscans=as.integer(10)

)

targetMz <- cbind(mz=c(560.6, 700.5, 933.7), z=rep(1, 3))common <- list(

OrbitrapResolution="R120K",IsolationWindow=1,MaxITTimeInMS=200,Microscans=as.integer(40),AgcTarget=c(1e5, 5e5, 1e6)

)

cid <- expandTms2Conditions(MassList=targetMz,common,ActivationType="CID",CIDCollisionEnergy=seq(7, 35, 7)

)hcd <- expandTms2Conditions(

MassList=targetMz,common,

createExperimentsFragmentOptimisation 9

ActivationType="HCD",HCDCollisionEnergy=seq(7, 35, 7)

)etd <- expandTms2Conditions(

MassList=targetMz,common,ActivationType="ETD",ETDReactionTime=as.double(1:2)

)etcid <- expandTms2Conditions(

MassList=targetMz,common,ActivationType="ETD",ETDReactionTime=as.double(1:2),ETDSupplementalActivation="ETciD",ETDSupplementalActivationEnergy=as.double(1:2)

)uvpd <- expandTms2Conditions(

MassList=targetMz,common,ActivationType="UVPD"

)

exps <- createExperimentsFragmentOptimisation(ms1=ms1, cid, hcd, etd, etcid, uvpd,groupBy=c("AgcTarget", "replication"), nMs2perMs1=10, scanDuration=0.5,replications=2, randomise=TRUE

)

## use different settings for CIDcid560 <- expandTms2Conditions(

MassList=cbind(560.6, 1),common,ActivationType="CID",CIDCollisionEnergy=seq(7, 21, 7)

)cid700 <- expandTms2Conditions(

MassList=cbind(700.5, 1),common,ActivationType="CID",CIDCollisionEnergy=seq(21, 35, 7)

)

exps <- createExperimentsFragmentOptimisation(ms1=ms1, cid560, cid700,groupBy=c("AgcTarget", "replication"), nMs2perMs1=10, scanDuration=0.5,replications=2, randomise=TRUE

)

## use a CSV (or excel) file as inputmyCsvContent <- "ActivationType, ETDReactionTime, UVPDActivationTimeUVPD,,1000ETD,1000,"myCsvSettings <- read.csv(text=myCsvContent, stringsAsFactors=FALSE)myCsvSettings

10 createTngFusionMethFiles

# ActivationType ETDReactionTime UVPDActivationTime# 1 UVPD NA 1000# 2 ETD 1000 NA

exps <- createExperimentsFragmentOptimisation(ms1 = data.frame(FirstMass=500, LastMass=1000),## TMS2myCsvSettings,## other argumentsgroupBy="ActivationType"

)

createTngFusionMethFiles

Windows specific functions.

Description

The functions runXmlMethodChanger and runScanHeadsman call XmlMethodChanger.exe andScanHeadsman.exe with the corresponding arguments. The only work on Windows (maybe onLinux + wine as well but that was never tested).

Usage

createTngFusionMethFiles(template,xml = list.files(pattern = ".*\\.xml$"),executable = "XmlMethodChanger.exe",verbose = interactive()

)

runXmlMethodChanger(template,xml = list.files(pattern = ".*\\.xml$"),executable = "XmlMethodChanger.exe",verbose = interactive()

)

runScanHeadsman(path = ".", executable = "ScanHeadsman.exe")

Arguments

template character, path to template .meth file.

xml character, vector of path to .xml files.

executable character, path to the XmlMethodChanger.exe or ScanHeadsman.exe exe-cutable.

verbose logical, if TRUE a progress bar is shown.

path character, path to the directory containing the .raw files.

expandMs1Conditions 11

Details

runXmlMethodChanger applies ‘XmlMethodChanger.exe’ on all given XML files generated withwriteMethodXmls() to create .meth files from a template.

runScanHeadsman calls ScanHeadsman.exe on a given directory containing .raw files. ScanHeadsman.exeextracts the method and scan header data into .experiments.csv and .txt files, respectively.

Value

Nothing. Used for its side effects.

References

XmlMethodChanger source code: https://github.com/thermofisherlsms/meth-modifications/

ScanHeadsman source code: https://bitbucket.org/caetera/scanheadsman

See Also

writeMethodXmls()

Examples

## Not run:runXmlMethodChanger(templateMeth="TMS2IndependentTemplate240Extended.meth",

modificationXml=list.files(pattern="^method.*\\.xml$"),executable="..\\XmlMethodChanger.exe")

## End(Not run)## Not run:runScanHeadsman("raw", executable="..\\ScanHeadsman.exe")

## End(Not run)

expandMs1Conditions Expand MS Conditions

Description

Create a data.frame of all possible combinations of the given arguments. It ensures that justarguments are applied that yield a valid MethodModification.xml file.

Usage

expandMs1Conditions(..., family = "Calcium", version = "3.2")

expandTms2Conditions(ActivationType = c("CID", "HCD", "ETD", "UVPD"),...,MassList = NULL,family = "Calcium",version = "3.2"

)

12 FragmentViews-class

Arguments

... further named arguments, used to create the combination of conditions.

family character, currently just Calcium is supported

version character, currently 3.1, 3.2 (default), 3.3 are supported

ActivationType character, ActivationType for TMS2, either CID, HCD, ETD, or UVPD.

MassList matrix, 2 columns (mass, z) for targeted mass list, or NULL (default) to notoverwrite targeted mass.

Value

data.frame with all possible combinations of conditions/settings.

See Also

validMs1Settings()

validTms2Settings(), expand.grid()

Examples

expandMs1Conditions(FirstMass=100, LastMass=400)expandTms2Conditions(

ActivationType="CID",OrbitrapResolution="R120K",IsolationWindow=1,MaxITTimeInMS=200,Microscans=as.integer(40),AgcTarget=c(1e5, 5e5, 1e6),CIDCollisionEnergy=c(NA, seq(7, 35, 7)),MassList=cbind(mz=c(560.6, 700.5, 933.7), z=rep(1, 3))

)

FragmentViews-class The FragmentViews class

Description

The FragmentViews class is a basic container for storing a set of views (start/end locations) on thesame peptides/protein sequence. Additionally it keeps information about mass, type and charge ofthe fragments.

Usage

FragmentViews(sequence,mass,type,z = 1L,start = NULL,end = NULL,width = NULL,

FragmentViews-class 13

names = NULL,metadata = list()

)

## S4 method for signature 'FragmentViews,FragmentViews'combine(x, y)

## S4 method for signature 'FragmentViews'mz(object, ...)

## S4 method for signature 'FragmentViews'show(object)

Arguments

sequence character/ Biostrings::AAString, complete protein/peptide sequence.

mass double, mass of the fragments, same length as start/end/width.

type character, type of the fragments, same length as start/end/width‘.

z integer, charge of the fragments, length one or same length as start/end/width‘.

start integer, start positions of the fragments. At least two of start/end/width‘ hasto be given.

end integer, end positions of the fragments. At least two of start/end/width‘ hasto be given.

width integer, width positions of the fragments. At least two of start/end/width‘has to be given.

names character, names of the fragments, same length as start/end/width‘.

metadata list, metadata like modifications.

object, x, y FragmentViews

... arguments passed to internal/other methods.

Details

FragmentViews extends Biostrings::XStringViews. In short it combines an IRanges::IRanges objectto store start/end location on a sequence, an Biostrings::AAString object.

Value

An FragmentViews object.

Functions

• FragmentViews: ConstructorIn general it is not necessary to call the constructor manually. See readTopDownFiles()instead.

Coercion

as(object,"data.frame"): Coerce an FragmentViews object into a data.frame.

14 NCBSet-class

Author(s)


See Also

Biostrings::XStringViews

Examples

# Constructorfv <- FragmentViews("ACE", start=1, width=1:3, names=paste0("b", 1:3),

mass=c(72.04439, 232.07504, 361.11763),type="b", z=1)

fv

# Coercion to data.frameas(fv, "data.frame")as(fv, "data.frame")

NCBSet-class The NCBSet class

Description

The NCBSet class is a container for a top-down proteomics experiment similar to the TopDownSetbut instead of intensity values it just stores the information if a bond is covered by a N-terminal(encoded as 1), a C-terminal (encoded as 2) and/or bidirectional fragments (encoded as 3).

Usage

## S4 method for signature 'NCBSet'bestConditions(object,n = ncol(object),minN = 0L,maximise = c("fragments", "bonds"),...

)

## S4 method for signature 'NCBSet'fragmentationMap(object,nCombinations = 10,cumCoverage = TRUE,maximise = c("fragments", "bonds"),labels = colnames(object),alphaIntensity = TRUE,...

)

## S4 method for signature 'NCBSet'show(object)

NCBSet-class 15

## S4 method for signature 'NCBSet'summary(object, what = c("conditions", "bonds"), ...)

Arguments

object NCBSet

n integer, max number of combinations/iterations.

minN integer, stop if there are less than minN additional fragments

maximise character, optimisation targeting for the highest number of "fragments" (de-fault) or "bonds".

nCombinations integer, number of combinations to show (0 to avoid plotting them at all).

cumCoverage logical, if TRUE (default) cumulative coverage of combinations is shown.

labels character, overwrite x-axis labels.

alphaIntensity logical, if TRUE (default) the alpha level of the color is used to show thecolData(object)$AssignedIntensity. If FALSE the alpha is set to 1.

what character, specifies whether "conditions" (columns; default) or "bonds"(rows) should be summarized.

... arguments passed to internal/other methods. added.

Value

An NCBSet object.


• bestConditions: Best combination of conditions.Finds the best combination of conditions for highest coverage of fragments or bonds. If thereare two (or more conditions) that would add the same number of fragments/bonds the one withthe highest assigned intensity is used. Use n to limit the number of iterations and combina-tions that should be returned. If minN is set at least minN fragments have to be added to thecombinations. The function returns a 7-column matrix. The first column contains the index(Index) of the condition (column number). The next columns contain the newly added num-ber of fragments or bonds (FragmentsAddedToCombination, BondsAddedToCombination),the fragments or bonds in the condition (FragmentsInCondition, BondsInCondition), andthe cumulative coverage fragments or bonds (FragmentCoverage, BondCoverage).

• fragmentationMap: Plot fragmentation map.Plots a fragmentation map of the Protein. Use nCombinations to add another plot withnCombinations combined conditions. If cumCoverage is TRUE (default) these combinationsincrease the coverage cumulatively.

• summary: Summary statistics.Returns a matrix with some statistics: number of fragments, total/min/first quartile/median/mean/thirdquartile/maximum of intensity values.

Slots

rowViews Biostrings::XStringViews, information about bonds (name, start, end, width, sequence),see Biostrings::XStringViews for details.


16 NCBSet-class

assay Matrix::dgCMatrix, coverage values of the bonds. The rows correspond to the bonds andthe columns to the condition/run. It just stores values that are different from zero. If a bond iscovered by an N-terminal fragment its encoded with 1, by an C-terminal fragmentl with 2 andby both fragment types/bidirectional by 3 respectively.

files character, files that were imported.

processing character, log messages.

Author(s)


See Also

• An NCBSet is generated from an TopDownSet object.

• Biostrings::XStringViews for the row view interface.

• Matrix::dgCMatrix for technical details about the coverage storage.

Examples


## Aggregate technical replicatestds <- aggregate(tds)

## Coercion into an NCBSet objectncb <- as(tds, "NCBSet")

ncb

head(summary(ncb))

# Accessing slotsrowViews(ncb)colData(ncb)head(assayData(ncb))

# Accessing colDatancb$Mz

# Subsetting

# First 100 bondsncb[1:100]

# Just bond 152ncb["bond152"]

# Condition 1 to 10ncb[, 1:10]

# Plot fragmentation mapfragmentationMap(ncb)

readTopDownFiles 17

readTopDownFiles Read top-down files.

Description

It creates an TopDownSet object and is its only constructor.

Usage

readTopDownFiles(path,pattern = ".*",type = c("a", "b", "c", "x", "y", "z"),modifications = c("Carbamidomethyl", "Acetyl", "Met-loss"),adducts = data.frame(),neutralLoss = MSnbase::defaultNeutralLoss(),sequenceOrder = c("original", "random", "inverse"),tolerance = 5e-06,redundantIonMatch = c("remove", "closest"),redundantFragmentMatch = c("remove", "closest"),dropNonInformativeColumns = TRUE,sampleColumns = c("Mz", "AgcTarget", "EtdReagentTarget", "EtdActivation","CidActivation", "HcdActivation", "UvpdActivation"),

conditions = "ScanDescription",verbose = interactive()

)

Arguments

path character, path to directory that contains the top-down files.

pattern character, a filename pattern, the default .* means all files.

type character, type of fragments, currently a-c and x-z are supported, see MSnbase::calculateFragments()for details.

modifications character, unimod names of modifications that should be applied. Currenltyjust Acetyl (Unimod:1 but just protein N-term), Carbamidomethyl (Unimod:4)and Met-loss (Unimod:765) are supported. Met-loss removes M (if followed byA, C, G, P, S, T, or V; (see also http://www.unimod.org/modifications_view.php?editid1=1,http://www.unimod.org/modifications_view.php?editid1=4, and http://www.unimod.org/modifications_view.php?editid1=765for details)). Use NULL to disable all modifications.

adducts data.frame, with 3 columns, namely: mass, name, to, see details section.

neutralLoss list, neutral loss that should be applied, see MSnbase::calculateFragments()and MSnbase::defaultNeutralLoss() for details.

sequenceOrder character, order of the sequence before fragment calculation and matching isdone. "original" doesn’t change anything. "inverse" reverse the sequenceand "random" arranges the amino acid sequence at random.

tolerance double, tolerance in ppm that is used to match the theoretical fragments withthe observed ones.

18 readTopDownFiles

redundantIonMatch

character, a mz could be matched to one, two or more fragments. If it ismatched against more than one fragment the match could be "remove"d or thematch to the "closest" fragment could be chosen.

redundantFragmentMatch

character, one or more mz could be matched to the same fragment, thesematches could be "remove"d or the match to the "closest" mz is chosen.

dropNonInformativeColumns

logical, should columns with just one identical value across all runs be removed?

sampleColumns character, column names of the colData() used to define a sample (technicalreplicate). This is used to add the Sample column (used for easier aggregation,etc.).

conditions character/numeric, one of:

• "ScanDescription" (default): create condition IDs based on the given"Scan Description" parameter (set automatically by createExperimentsFragmentOptimisation()).

• "FilterString": create condition IDs based on mass labels in the Filter-String column (included for backward-compatibilty, used in writeMethodXmls()prior version 1.5.2 in Dec 2018).

• A single numeric value giving the number of conditions.


Details

readTopDownFiles reads and processes all top-down files, namely:

• .fasta (protein sequence)

• .mzML (spectra)

• .experiments.csv (method/fragmentation conditions)

• .txt (scan header information)

adducts: Thermo’s Xtract allows some mistakes in deisotoping, mostly it allows +/- C13-C12 and+/- H+. The adducts argument takes a data.frame with the mass to add, the name that shouldassign to these new fragments and an information to whom the modification should be applied, e.g.for H+ on z, data.frame(mass=1.008,name="zpH",to="z").

Please note: The adducts are added to the output of MSnbase::calculateFragments(). That hassome limitations, e.g. neutral loss calculation could not be done in topdownr-package. If neutral lossshould be applied on adducts you have to create additional rows, e.g.: data.frame(mass=c(1.008,1.008),name=c("cpH","cpH_"),to=c("c","c_")).

Value

A TopDownSet object.

See Also

MSnbase::calculateFragments(), MSnbase::defaultNeutralLoss()

tds 19

Examples

if (require("topdownrdata")) {# add H+ to z and no neutral loss of watertds <- readTopDownFiles(

topdownrdata::topDownDataPath("myoglobin"),## Use an artifical pattern to load just the fasta## file and files from m/z == 1211, ETD reagent## target 1e6 and first replicate to keep runtime## of the example shortpattern=".*fasta.gz$|1211_.*1e6_1",adducts=data.frame(mass=1.008, name="zpH", to="z"),neutralLoss=MSnbase::defaultNeutralLoss(

disableWaterLoss=c("Cterm", "D", "E", "S", "T")),tolerance=25e-6

)}

tds TopDownSet Example Data

Description

An example data set for topdownr. It is just a subset of the myoglobin dataset available in topdownrdata::topdownrdata-package.

Usage

tds

Format

A TopDownSet with 14901 fragments (1949 rows, 351 columns).

Details

It was created as follows:

tds <- readTopDownFiles(topdownrdata::topDownDataPath("myoglobin"),## Use an artifical pattern to load just the fasta## file and files from m/z == 1211, ETD reagent## target 1e6 and first replicate to keep runtime## of the example shortpattern=".*fasta.gz$|1211_.*1e6_1",adducts=data.frame(mass=1.008, name="zpH", to="z"),neutralLoss=MSnbase::defaultNeutralLoss(

disableWaterLoss=c("Cterm", "D", "E", "S", "T")),tolerance=25e-6)

Source

Subset taken from the topdownrdata::topdownrdata-package package.

20 TopDownSet-class

topdownr-deprecated Deprecated functions in topdownr

Description

These functions are provided for compatibility with older versions of ‘MyPkg’ only, and will bedefunct at the next release.

Details

The following functions are deprecated and will be made defunct; use the replacement indicatedbelow:

• defaultMs1Settings: expandMs1Conditions() in combination with createExperimentsFragmentOptimisation()

• defaultMs2Settings: expandTms2Conditions() in combination with createExperimentsFragmentOptimisation()

TopDownSet-class The TopDownSet class

Description

The TopDownSet class is a container for a whole top-down proteomics experiment.

Usage

## S4 method for signature 'TopDownSet'aggregate(x, by = x$Sample, ...)

## S4 method for signature 'TopDownSet,TopDownSet'combine(x, y)

## S4 method for signature 'TopDownSet'filterCv(object, threshold, by = object$Sample, ...)

## S4 method for signature 'TopDownSet'filterInjectionTime(object,maxDeviation = log2(3),keepTopN = 2,by = object$Sample,...

)

## S4 method for signature 'TopDownSet'filterIntensity(object, threshold, relative = TRUE, ...)

## S4 method for signature 'TopDownSet'filterNonReplicatedFragments(object, minN = 2, by = object$Sample, ...)

TopDownSet-class 21

## S4 method for signature 'TopDownSet'normalize(object, method = "TIC", ...)

## S4 method for signature 'TopDownSet,missing'plot(x, y, ..., verbose = interactive())

## S4 method for signature 'TopDownSet'show(object)

## S4 method for signature 'TopDownSet'summary(object, what = c("conditions", "fragments"), ...)

Arguments

x, object TopDownSet

by list, grouping variable, in general it refers to technical

y missing, not used.

threshold double, threshold variable.

maxDeviation double, maximal allowed deviation in the log2 injection time in ms in compar-ison to the median ion injection time.

keepTopN integer, how many technical replicates should be kept?

relative logical, if relative is TRUE all fragments with intensity below threshold *max(intensity) per fragment are removed, otherwise all fragments below thresholdare removed.

minN numeric, if less than minN of a fragment are found across technical replicates itis removed.

method character, normalisation method, currently just "TIC" for Total Ion Currentnormalisation of the scans/conditions (column-wise normalisation) is supported.


what character, specifies whether "conditions" (columns; default) or "fragments"(rows) should be summarized.

... arguments passed to internal/other methods. replicates (that’s why the default isthe "Sample" column in colData).

Details

See vignette("analysis",package="topdownr") for a detailed example how to work with TopDownSetobjects.

Value

An TopDownSet object.


• aggregate: Aggregate conditions/runs.Aggregates conditions/runs (columns) in an TopDownSet object by a user-given value (defaultis the "Sample" column of colData which has the same value for technical replicates). Itcombines intensity values and numeric metadata of the grouped conditions/runs (columns) bymean and returns a reduced TopDownSet object.

22 TopDownSet-class

• combine: Combine TopDownSet objects.combine allows to combine two or more TopDownSet objects. Please note that it uses thedefault sampleColumns to define technical replicates (see readTopDownFiles()).and the de-fault by argument to group ion injection times for the calculation of the median time (seeupdateMedianInjectionTime()). Both could be modified after combine by calling updateConditionNames()(with modified sampleColumns argument) and updateMedianInjectionTime() (with mod-ified by argument).

• filterCv: Filter by CV.Filtering is done by coefficient of variation across technical replicates (defined by the by argu-ment). All fragments below a given threshold are removed. The threshold is the maximalallowed CV in percent (sd/mean * 100 < threshold).

• filterInjectionTime: Filter by ion injection time.Filtering is done by maximal allowed deviation and just the technical keepTopN replicateswith the lowest deviation from the median ion injection time are kept.

• filterIntensity: Filter by intensity.Filtering is done by removing all fragments that are below a given (absolute/relative) intensitythreshold.

• filterNonReplicatedFragments: Filter by non-replicated fragments.Filtering is done by removing all fragments that don’t replicate across technical replicates.

• normalize: Normalise.Applies Total Ion Current normalisation to a TopDownSet object. The normalisation ist doneper scans/conditions (column-wise normalisation).

• plot: Plotting.Plots an TopDownSet object. The function returns a list of ggplot objects (one item percondtion). Use pdf or another non-interactive device to plot the list of ggplot objects (seeexample section).

• summary: Summary statistics.Returns a matrix with some statistics: number of fragments, total/min/first quartile/median/mean/thirdquartile/maximum of intensity values.

Slots

rowViews FragmentViews, information about fragments (name, type, sequence, mass, charge), seeFragmentViews for details.


assay Matrix::dgCMatrix, intensity values of the fragments. The rows correspond to the fragmentsand the columns to the condition/run. It just stores values that are different from zero.

files character, files that were imported.tolerance double, tolerance in ppm that were used for matching the experimental mz values to

the theoretical fragments.redundantMatching character, matching strategies for redundant ion/fragment matches. See

redundantIonMatch and redundantFragmentMatch in readTopDownFiles() for details.processing character, log messages.

Coercion

‘as(object, "MSnSet"): Coerce an TopDownSet object into an MSnbase::MSnSet object.

‘as(object, "NCBSet"): Coerce an TopDownSet object into an NCBSet object.

TopDownSet-class 23

Author(s)


See Also

• FragmentViews for the row view interface.

• Matrix::dgCMatrix for technical details about the intensity storage.

• ?vignette("analysis",package="topdownr") for a full documented example of an anal-ysis using topdownr.

Examples


tds

head(summary(tds))

# Accessing slotsrowViews(tds)colData(tds)head(assayData(tds))

# Accessing colDatatds$Mztds$FilterString

# Subsetting

# First 100 fragmentstds[1:100]

# All c fragmentstds["c"]

# Just c 152tds["c152"]

# Condition 1 to 10tds[, 1:10]

# Filtering# Filter all intensities that don't have at least 10 % of the highest# intensity per fragment.tds <- filterIntensity(tds, threshold=0.1)

# Filter all conditions with a CV above 30 % (across technical replicates)tds <- filterCv(tds, threshold=30)

# Filter all conditions with a large deviation in injection timetds <- filterInjectionTime(tds, maxDeviation=log2(3), keepTopN=2)

# Filter all conditions where fragments don't replicatetds <- filterNonReplicatedFragments(tds)

24 validMs1Settings

# Normalise by TICtds <- normalize(tds)

# Aggregate technical replicatestds <- aggregate(tds)

head(summary(tds))

# Coercionas(tds, "NCBSet")

if (require("MSnbase")) {as(tds, "MSnSet")

}## Not run:# plot a single condition# pseudo-code (replace topdownset with your object)plot(topdownset[,1])

# plot the whole objectpdf("topdown-spectra.pdf", paper="a4r", width=12)# pseudo-code (replace topdownset with your object)plot(topdownset)dev.off()

## End(Not run)

validMs1Settings List valid MS settings.

Description

These functions list settings for MS1 or TMS2 that are supported by Thermo’s XmlMethodChanger.

Usage

validMs1Settings(family = "Calcium", version = "3.2")

validTms2Settings(type = c("All", "TMS2", "ETD", "CID", "HCD", "UVPD"),family = "Calcium",version = "3.2"

)

Arguments

family character, currently just Calcium is supported

version character, currently 3.1, 3.2 (default), 3.3 are supported

type character, type of activation.

writeMethodXmls 25

Value

matrix with three columns:

• name: element name• class: expected R class of the value• type: MS/ActivationType, e.g. MS1/TMS2/ETD/...

Examples

validMs1Settings()validTms2Settings()validTms2Settings("TMS2")validTms2Settings("ETD")validTms2Settings(c("TMS2", "ETD"))

writeMethodXmls Create Orbitrap Fusion Lumos method.xml files.

Description

This function is used to create Orbitrap Fusion Lumos method files from a tree-like list experimentgenerated by e.g. createExperimentsFragmentOptimisation().

Usage

writeMethodXmls(exps, pattern = "method-%s.xml", verbose = interactive())

Arguments

exps list, generated by e.g. createExperimentsFragmentOptimisation()pattern character, file name pattern for the method.xml files.verbose logical, verbose output?

Details

• exps: a named tree-like list object generated by e.g. createExperimentsFragmentOptimisation().Its names are used as filename.

• pattern: The file name pattern used to name different method files. It must contain a "%s"that is replaced by the conditions defined in groupBy.

DEFUNCT options:

• ms1Settings: A list of MS1 settings. This has to be a named list. Valid MS1 settings are:c("FirstMass","LastMass","Microscans","MaxITTimeInMS","AgcTarget")

• ms2Settings: A list of MS2 settings. This has to be a named list. Valid MS2 settings are:c("ActivationType","IsolationWindow","EnableMultiplexIons","EnableMSXIds","MaxNoOfMultiplexIons","OrbitrapResolution","AgcTarget","MinAgcTarget","MaxITTimeInMS","Microscans","ETDReactionTime","ETDReagentTarget","MaximumETDReagentInjectionTime","UseInternalCalibratedETD","ETDSupplementalActivationEnergy","ETDSupplementalActivation")

• groupBy: The groupBy parameter is used to split methods into different files. Valid entriesare all settings that could be used in ms2Settings and "replication".

• massLabeling: The Orbitrap Fusion devices seems not to respect the start and end times ofthe runs given in the method.xml files. That’s why it is nearly impossible to identify the runwith its conditions based on the timings. If massLabeling is TRUE (default) the mass valuesgiven in mz are rounded to the first decimal place and the second to fourth decimal place isused as numeric identifier.

26 writeMethodXmls

Author(s)

Sebastian Gibb <[email protected]>, Pavel V. Shliaha <[email protected]>

See Also

createExperimentsFragmentOptimisation()

Examples

ms1 <- expandMs1Conditions(FirstMass=400, LastMass=1200, Microscans=as.integer(10))

targetMz <- cbind(mz=c(560.6, 700.5, 933.7), z=rep(1, 3))common <- list(

OrbitrapResolution="R120K",IsolationWindow=1,MaxITTimeInMS=200,Microscans=as.integer(40),AgcTarget=c(1e5, 5e5, 1e6)

)cid <- expandTms2Conditions(

MassList=targetMz,common,ActivationType="CID",CIDCollisionEnergy=seq(7, 35, 7)

)hcd <- expandTms2Conditions(

MassList=targetMz,common,ActivationType="HCD",HCDCollisionEnergy=seq(7, 35, 7)

)etd <- expandTms2Conditions(

MassList=targetMz,common,ActivationType="ETD",ETDReagentTarget=c(1e6, 5e6, 1e7),ETDReactionTime=c(2.5, 5, 10, 15, 30, 50),ETDSupplementalActivation=c("None", "ETciD", "EThcD"),ETDSupplementalActivationEnergy=seq(7, 35, 7)

)exps <- createExperimentsFragmentOptimisation(ms1=ms1, cid, hcd, etd,

groupBy=c("AgcTarget", "replication"), nMs2perMs1=10, scanDuration=0.5,replications=2, randomise=TRUE

)writeMethodXmls(exps=exps)

Index

∗ datasetstds, 19

∗ deprecatedtopdownr-deprecated, 20

∗ packagetopdownr-deprecated, 20topdownr-package, 2

[,AbstractTopDownSet,ANY,ANY,ANY-method(AbstractTopDownSet-class), 3

[[,AbstractTopDownSet,ANY,missing,-method(AbstractTopDownSet-class), 3

[[,AbstractTopDownSet,ANY,missing-method(AbstractTopDownSet-class), 3

[[<-,AbstractTopDownSet,ANY,missing,-method(AbstractTopDownSet-class), 3

[[<-,AbstractTopDownSet,ANY,missing-method(AbstractTopDownSet-class), 3

$,AbstractTopDownSet-method(AbstractTopDownSet-class), 3

$<-,AbstractTopDownSet-method(AbstractTopDownSet-class), 3

AbstractTopDownSet, 5, 6AbstractTopDownSet-class, 3aggregate,TopDownSet-method

(TopDownSet-class), 20assayData,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3

bestConditions (NCBSet-class), 14bestConditions,NCBSet-method

(NCBSet-class), 14Biostrings::AAString, 13Biostrings::XStringViews, 6, 13–16

coerce,FragmentViews,data.frame-method(FragmentViews-class), 12

coerce,TopDownSet,MSnSet-method(TopDownSet-class), 20

coerce,TopDownSet,NCBSet-method(TopDownSet-class), 20

colData (AbstractTopDownSet-class), 3colData(), 4, 18

colData,AbstractTopDownSet-method(AbstractTopDownSet-class), 3

colData<- (AbstractTopDownSet-class), 3colData<-,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3combine (AbstractTopDownSet-class), 3combine,AbstractTopDownSet,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3combine,FragmentViews,FragmentViews-method

(FragmentViews-class), 12combine,FragmentViews-method

(FragmentViews-class), 12combine,TopDownSet,TopDownSet-method

(TopDownSet-class), 20conditionData

(AbstractTopDownSet-class), 3conditionData,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3conditionData<-

(AbstractTopDownSet-class), 3conditionData<-,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3conditionNames

(AbstractTopDownSet-class), 3conditionNames,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3createExperimentsFragmentOptimisation,

7createExperimentsFragmentOptimisation(),

18, 20, 25, 26createTngFusionMethFiles, 10

dim,AbstractTopDownSet-method(AbstractTopDownSet-class), 3

dimnames,AbstractTopDownSet-method(AbstractTopDownSet-class), 3

expand.grid(), 12expandMs1Conditions, 11expandMs1Conditions(), 8, 20expandTms2Conditions

(expandMs1Conditions), 11expandTms2Conditions(), 8, 20

filterCv (TopDownSet-class), 20

27

28 INDEX

filterCv,TopDownSet-method(TopDownSet-class), 20

filterInjectionTime (TopDownSet-class),20

filterInjectionTime,TopDownSet-method(TopDownSet-class), 20

filterIntensity (TopDownSet-class), 20filterIntensity,TopDownSet-method

(TopDownSet-class), 20filterNonReplicatedFragments

(TopDownSet-class), 20filterNonReplicatedFragments,TopDownSet-method

(TopDownSet-class), 20fragmentationMap (NCBSet-class), 14fragmentationMap,NCBSet-method

(NCBSet-class), 14FragmentViews, 6, 13, 22, 23FragmentViews (FragmentViews-class), 12FragmentViews-class, 12

IRanges::IRanges, 13

Matrix::dgCMatrix, 5, 6, 16, 22, 23MSnbase::calculateFragments(), 17, 18MSnbase::defaultNeutralLoss(), 17, 18MSnbase::MSnSet, 22mz,FragmentViews-method

(FragmentViews-class), 12

NCBSet, 3, 5, 6, 15, 22NCBSet-class, 14normalize,TopDownSet-method

(TopDownSet-class), 20

plot,TopDownSet,missing-method(TopDownSet-class), 20

readTopDownFiles, 17readTopDownFiles(), 5, 13, 22removeEmptyConditions

(AbstractTopDownSet-class), 3removeEmptyConditions,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3rowViews (AbstractTopDownSet-class), 3rowViews,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3runScanHeadsman

(createTngFusionMethFiles), 10runXmlMethodChanger

(createTngFusionMethFiles), 10

S4Vectors::DataFrame, 5, 6, 15, 22show,AbstractTopDownSet-method


show,FragmentViews-method(FragmentViews-class), 12

show,NCBSet-method (NCBSet-class), 14show,TopDownSet-method

(TopDownSet-class), 20summary,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3summary,NCBSet-method (NCBSet-class), 14summary,TopDownSet-method

(TopDownSet-class), 20

tds, 19topdownr (topdownr-package), 2topdownr-deprecated, 20topdownr-package, 2, 18topdownrdata::topdownrdata-package, 19TopDownSet, 3–6, 14, 16, 17, 19, 21, 22TopDownSet-class, 20

updateConditionNames(AbstractTopDownSet-class), 3

updateConditionNames(), 5, 22updateConditionNames,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3updateMedianInjectionTime

(AbstractTopDownSet-class), 3updateMedianInjectionTime(), 5, 22updateMedianInjectionTime,AbstractTopDownSet-method

(AbstractTopDownSet-class), 3updateMedianInjectionTime,TopDownSet-method


validMs1Settings, 24validMs1Settings(), 12validTms2Settings (validMs1Settings), 24validTms2Settings(), 12

writeMethodXmls, 25writeMethodXmls(), 7, 8, 11, 18

xml2::as_xml_document(), 8

package ‘topdownr’ -...

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